MCPJam

RT @Prathmeshp_16: Show agents your MCP Apps UI with: mcpjam tools call --ui Coding agents can call a tool and see its UI rendered live in…

Inspect your MCP servers today with one command: mcpjam Our new @mcpjams CLI brings core Inspector workflows to your terminal: connect to servers, call tools, debug OAuth, and run protocol conformance. It also lets your coding agent debug MCP Apps by rendering tool results in the MCPJam UI! Pair it with our skill and get jamming: docs.mcpjam.com/cli/overview npm i -g @mcpjam/cli #mcp #modelcontextprotocol #cli

Solid high-level read. Personal takeaways: A great Day-1 guide on MCP tool design and best practices - but MCP client leaning as it doesn't address some immediate problems MCP servers will face in actually testing for natural questions that come with e.g. "but how do I know Skills + MCP is actually more effective for my server"? claude.com/blog/building-…

connect your MCP server → see a trace in 30 seconds tool calls, args, latency → all captured the moment you run. demo ↓ #mcp #modelcontextprotocol

I spoke at @mcpsummit in NY on "Evaluate What You Can't See." The core problem I discussed: your MCP server can execute perfectly and still fail the user. You have almost no visibility into it. Covered the User-Value Chain framework, why REST instincts don't transfer to MCP tool design, and 6 concrete ways to get user context in a system that hides it from you. Full 30-min talk: youtu.be/XqjOcKEUSRQ?si… #mcp #modelcontextprotocol @mcpjams

We just shipped two features I’ve wanted since debugging Asana’s MCP server: Trace Viewer - Visualize a trace across the user, agent, host application, and server with token usage, latency, payload details Multi-Model Compare - Send a single prompt to up to three models simultaneously (including frontier models like Opus 4.6, GPT-5.4, Gemini 3.1 Pro). Here’s what it looks like in 40 seconds. #mcp #modelcontextprotocol

Anthropic just launched Claude Managed Agents, making agent deployment much easier. Asana, Notion, Rakuten already shipping production agents on it. As the agent deployment deployment barrier gets lower: Agent-initiated traffic on your product may begin to outpace human-initiated traffic. Your MCP server works, but does it effectively deliver user value inside an agentic application environment you don't observe or control?

Most MCP integrations measure "did the tool call succeed?". Not "did the user get what they wanted?" Part 1 of our Effective MCP series breaks down why that gap exists and the full chain that has to hold to deliver real user value.